Standard Objection 1: "AI researchers have been promising imminent breakthroughs for the past 50 years. This is just another wildly optimistic prediction." Moravec's analysis notes that, although AI research has been conducted for 50 years, the amount of funding available to AI researchers has decreased dramatically, with the result that AI researchers have had nearly a constant amount of hardware power at their disposal until fairly recently. He also argues that AI strongly tracks advances in hardware --- the AI software you write for a 100-MIPS computer is not just a bigger, faster version of the software you write for a 1-MIPS computer, it's designed fundamentally differently. Multi-million-MIPS computers will enable vastly new approaches that enable quantum leaps in AI power.

Standard Objection 2: "Neurons are far more complex than is popularly believed. Your estimates of brain complexity are far too conservative." This is irrelevant to Moravec's analysis, which relies on an analysis of a functional unit of the nervous system, not raw neuron counts:

More computer power is needed to reach human performance, but how much? Human and animal brain sizes imply an answer, if we can relate nerve volume to computation. Structurally and functionally, one of the best understood neural assemblies is the retina of the vertebrate eye. Happily, similar operations have been developed for robot vision, handing us a rough conversion factor.

...

It takes robot vision programs about 100 computer instructions to derive single edge or motion detections from comparable video images. 100 million instructions are needed to do a million detections, and 1,000 MIPS to repeat them ten times per second to match the retina.

The 1,500 cubic centimeter human brain is about 100,000 times as large as the retina, suggesting that matching overall human behavior will take about 100 million MIPS of computer power.

In Moravec's analysis, it's irrelevant how computationally complex individual neurons are. The volume of neurons in the eye performs a visual processing task that can be simulated by 1,000 MIPS. Regardless of how these neurons accomplish this task, it appears that 1,000 MIPS is roughly adequate to replace the function of that volume of neural matter. It stands to reason that other functional units of the brain would require similar amounts of computing power per unit of volume.

Of course, neurons may be more densely packed and interconnected in the brain proper than in the retina, but probably not by more than an order of magnitude or two. Assuming continued exponential growth in computating hardware, a mere order of magnitude only signifies a few years' difference: perhaps it will take fifty-three years instead of fifty. Hardly a basis for pessimism.

I don't buy Moravec's analysis entirely (there are some obvious objections, although no fatally conclusive ones, to Moravec's analysis) but it's an interesting read nonetheless.